karlamonrealfandomcom_es-20200213-history
Net-Aware Theories of Learning
The Net context creates an environment that is radically different from pre-Net contexts, yet of course carries evolutionary genes from previous cultures and technologies. In 2004 Denise Whitelock and I edited a special edition of the ''Journal of Interactive Media in Education ''that focused on the educational semantic web (Anderson & Whitelock, 2004). In the introduction to this issue, we provided an overview of three affordances of the Web, which I still believe define its value for teaching and learning. The first is the capacity for powerful yet very low-cost communications. This capacity forms the platform upon which “epistemic-engagement” visions of learning are instantiated. This communication may be engaged in synchronous, asynchronous, or near-synchronous (as in text messaging) modes. Communications may be expressed through text, voice, video or even immersive interaction modes. These communication modes can also be combined in many creative ways. Communication artifacts can be stored, indexed, tagged, harvested, searched, and sorted. All of this capacity is available at low or (at least in parts of the world) affordable cost. Finally, net communications can be one to one, one to many, or many to many, with very little cost differentiation among the three modes. Thus, educators have moved away from a world in which communication was expensive, geographically restricted (often limited to those sharing the same classroom), and privileged (limited to those with production facilities). Moreover, net communications provide access to and empower those with hearing, movement, or visual impairments. These communications affordances obviously can be used in a multitude of ways in formal education and teaching (see chapters 4, 12, and 14). The recent emergence of social software sites affords learners the opportunity to seek and share questions, understandings, and resources, thus creating learner-organized tutoring and support opportunities (chapter 6). Perhaps most importantly, this communications capacity creates opportunities for many forms of collaborative informal and lifelong learning (Koper & Tattersall, 2004). The second affordance we discussed in 2004 is that the Net creates a context that moves us from information and content scarcity to abundance. From early-learning object repositories to wide-scale distribution and production of Open Educational Resources from many networked sites, the Net provides learning content with many different display and presentation attributes. This content exists in many formats, and often uses multimedia to enhance its presentational value. Most exciting is the capacity for learners and teachers to add user-created content and to edit and enhance the work of others using produsage production modes (Bruns, 2008). The third affordance we identified in 2004 has been less apparent, but still holds great promise for teaching and learning. This is the affordance of active and autonomous agents that can be set loose on the Net to gather, aggregate, synthesize, and filter the Net for content and communications that is relevant to individual and groups of learners and teachers. The educational semantic web still remains “just around the corner,” and there have been serious methodological (Doctorow, 2001) and epistemological (Kalfoglou, Schorlemmer, & Walton, 2004) challenges to its emergence. However, there is an increasing number of applications that utilize autonomous agents (Anderson, 2004a; Sloep et al., 2004) to induce and support learning. The most visible of these applications are the search-engine algorithms that we all use to find and retrieve Net-based content, products, and services. By noting which sites are selected most often and which have the most established traffic and links, search engines calculate short lists of options to select from among the often millions of matches that are found — and as often as not the “correct” site appears among those on the first result screen. Through agents actively monitoring the Net, the links, and the collective actions of users, algorithms produce an intelligent guess as to the searcher’s desired result — as well as a few targeted advertisements! Furthermore, agents monitoring these searches extract additional information that is used by marketers and social researchers to further understand our collective ideas, choices, and interests (Tancer, 2008), as well as by researchers and educators who want to further understand learner behavior in Net-based learning environments (chapter 12). Netbased agents will doubtlessly continue to add value to all three of the visions for educational technology, including presentation, performancetutoring, and epistemic engagement. Nevertheless, being in awe of stunning technical affordances does little to direct or help us to understand teaching and learning. For this, I end the chapter with overviews of three more recent learning theories that evolved in the technology-enhanced learning networked area.